View source: R/checkpoints_qreg_4D.R
checkpoints_qreg_4D | R Documentation |
This function checks whether points belong to quantile regions or not, based on estimated models for models with 4 dimensions.
checkpoints_qreg_4D(
model,
datafile,
response,
points_y,
x_values = 1,
path_folder = NULL,
splines_part = FALSE,
w_values = NULL,
model_name = "bayesx.estim",
name_var,
adaptive_dir = FALSE,
upperq = FALSE,
lowerq = FALSE,
...
)
model |
This is an object of the class |
datafile |
A data.frame from which to find the variables defined in the formula. |
response |
Names of response variables |
points_y |
the exact points in Y, in which one wants to find its respective quantile region. |
x_values |
Fixed value of the predictor variables. |
path_folder |
The path where all results are stored. |
splines_part |
Logical value to indicate whether there are splines terms in the equation to draw the quantile contours. |
w_values |
Value to be considered in the nonlinear part of the model. |
model_name |
When results will be collected in a folder, this should be the name of the name considered by BayesX to save all tables. Default is 'bayesx.estim'. |
name_var |
When there is a nonlinear variable from which one wants to consider different values for plotting, this should have the name of the variable. |
adaptive_dir |
If |
upperq |
If TRUE, then it will take into account the upper quantiles for each coefficient of the model. |
lowerq |
If TRUE, then it will take into account the lower quantiles for each coefficient of the model. |
... |
Other parameters for |
A ggplot with the quantile regions based on Bayesian quantile regression model estimates.
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